Forecasting India's Electricity Consumption Using Particle Swarm Optimization

被引：2
|
作者：
Saravanan, S. [1 ]
Nithya, R. [1 ]
Kannan, S. [1 ]
Thangaraj, C. [2 ]
机构：
[1] Kalasalingam Univ, Krishnankoil, Tamil Nadu, India
[2] Anna Univ Technol, Madras, Tamil Nadu, India
来源：
POWER ELECTRONICS AND RENEWABLE ENERGY SYSTEMS | 2015年 / 326卷
关键词：
Particle swarm optimization (PSO); Mean absolute percentage error (MAPE); Electricity consumption; ENERGY DEMAND; TURKEY; INTELLIGENCE; PREDICTION; ALGORITHM;
D O I：
10.1007/978-81-322-2119-7_82
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper uses Particle Swarm Optimization (PSO) technique to estimate the electricity consumption in India, based on economic indicators. The data used to estimate the consumption are non-linear. An exponential model is developed and applied to forecast the electricity consumption based on the economic indicators such as population, per capita Gross Domestic Product (GDP), import and export data. The available data are partly used for training the model (1975-2000) and remaining used for testing the model (2000-2010). Mean Absolute Percentage Error (MAPE) is used as an evaluation criterion for finding the future electricity consumption up to the year 2025. The results are compared with the 18th Electric Power Survey of India.
引用
收藏
页码：843 / 851
页数：9
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